摘要
针对单配送中心带时间窗的车辆路径问题,将时间约束折算为惩罚费用,在时间、车辆体积和载重约束的条件下,建立了一种带软时间窗的物流车辆路径总费用最小数学模型。同时在遗传算法的基础上加入记忆功能和退火操作,采用带有记忆的遗传模拟退火算法求解此模型,并将优化结果进行比较。结果表明,该算法收敛速度快、搜索领域宽,能取得较高质量的最优解。
We construct a soft time window associated mathematical model minimizing total vehicle routing cost by converting time constraint into penalty cost under the constraint of time,vehicle volume and vehicle carrying capacity in view of time window associated vehicle routing issue in a single distribution center.We employ memory dependent genetic simulated annealing algorithm （GSAA） to solve the model,which adds memory functionality and annealing operation to a genetic algorithm.We further compare optimized results.Results show that the algorithm has quick convergence rate,broad search scope and higher-quality optimization solution.
出处
《山东科学》
CAS
2013年第5期104-110,共7页
Shandong Science
关键词
车辆路径问题
时间窗
数学模型
遗传模拟退火算法
vehicle routing problem
time window
mathematical model
genetic simulated annealing algorithm
